The rapid transition to digital has significantly changed the world forever. Traditional voice and text businesses are declining as the data business grows exponentially. The competition has broadened to include new kinds of business models. Customer’s expectations are very different. Organizations need to renovate, innovate and evolve much faster than ever before to stay relevant.
Businesses in consumer facing industries are investing colossal amounts of money in digital and analytics to modernize and monetize service operations. There is a constant battle to breakeven at the earliest and start generating profits. In this context, businesses need to alter their operating model by harnessing digital technologies that augment and power up most of their operations. Organizations must find ways to improve Average Revenue Per Customer (ARPC), without losing much capital and yet provide stellar customer satisfaction that just doesn’t translate to mere touch and go experiences, but turn customers into brand loyalists and advocates.
The message is clear. Traditional ways of customer engagement and forecasting don’t work anymore. Businesses need insights and actions to flawlessly execute, automate and orchestrate business processes. But where do you get these insights? The answer to that is within your own ecosystem. Your data.
By leveraging data analytics laced with Artificial Intelligence, organizations can find, generate patterns from the humongous data sets that they produce. Based on these patterns, insights can be generated, predictability becomes stronger and there are no more guesses. It becomes a magnifying glass that helps you microscopically view your data, patterns and intent so that you can drive predictive decisions way before competition does. It helps you speed up business operations.
In the digital world, data is the new currency and that’s what businesses need to see as their treasure. Analyzing data over time gives sharp insights into business operations. If it is customer data we are looking at, answers to the questions below could be a goldmine for brands:
- How are customer expectations changing?
- What are their interests?
- What is their spending rate?
- Where are they going to spend next?
- Upto what percentage would they spend and so on
This can be a great source of information for online marketing functions who can then fine tune their campaigns accordingly. This helps the marketers understand their consumer base and the end consumer feels happy that his needs are being personalized.
Similarly, analyzing customer support operations can throw interesting details like:
- The overall user base of a product
- Customer feedback of the product
- Customer service calls and records
- Product usage details
- Sales and billing history
- Warranty details
Having known this side of data, we can apply this aspect of data analytics to any business operation – right from marketing to sales to customer experience to almost any aspect of business function/industry/service. Adopting a data driven approach helps organizations unify customer view, giving organizations better integration between business units, better reliability and functionality. Overall, operations become easier to manage as everything is accounted for and is available real-time.
Armed with the power of data analytics, we are enabling and transforming technical support operations for a large enterprise networking major. Being a support center for complex networking products, their engineers were flooded with calls. They had their own mechanisms that provided control but it wasn’t much to their expectations. They embarked on a mission to see if they can turn around support operations digitally. Using our Early Warning System(EWS), we ported data from their CRMs including data from emails, call logs and chat. The platform digested data from multiple sources, made inferences, and produced actionable insights which were viewed on a real-time dashboard This enabled support engineers get a 360-degree view of operations, helped them take timely decisions on support cases, manage the floor better (engineer allotments) and plan for escalations in a prepared manner. The dashboard helped engineers understand the time taken for case resolutions more clearly.
The most important takeaway from this implementation is that it gives critical insights into case history. The amount of time for case resolution, what are the factors that lengthen a case, are there ways to shorten this process by automation or relooking manual tasks? The culmination of these operational insights increases customer experience as support calls now close faster, resolutions are immediate and both parties are happy. It strengthens support engineers as they are more confident, and ready to take on more cases as they grow better with time.
Conclusion
Today, businesses have realized that data is a game changer. The more you mine and hone it, the better you stand out from competition. In this aspect, it is prudent for every organization thriving in the digital age to have a strong analytical platform backing their operations, as it can turn around business functions deliver superior customer experiences.
